English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We consider a mean-field model for large banking systems, which takes intoaccount default and recovery of the institutions. Building on models used forgroups of interacting neurons, we first study a McKean-Vlasov dynamics and itsevolutionary Fokker-Planck equation in which the mean-field interactions occurthrough a mean-reverting term and through a hitting time corresponding to adefault level. The latter feature reflects the impact of a financialinstitution's default on the global distribution of reserves in the bankingsystem. The systemic risk problem of financial institutions is understood as ablow-up phenomenon of the Fokker-Planck equation. Then, we incorporate in themodel an optimization component by letting the institutions control part oftheir dynamics in order to minimize their expected risk. Phrasing thisoptimization problem as a mean-field game, we provide an explicit solution in aspecial case and, in the general case, we report numerical experiments based ona finite difference scheme.

Large Banking Systems with Default and Recovery: A Mean Field Game Model